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Effects of a Trust Mechanism on Complex Adaptive Supply Networks: An Agent-Based Social Simulation Study

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  • Whan-Seon Kim

Abstract

This paper models a supply network as a complex adaptive system (CAS), in which firms or agents interact with one another and adapt themselves. And it applies agent-based social simulation (ABSS), a research method of simulating social systems under the CAS paradigm, to observe emergent outcomes. The main purposes of this paper are to consider a social factor, trust, in modeling the agents' behavioral decision-makings and, through the simulation studies, to examine the intermediate self-organizing processes and the resulting macro-level system behaviors. The simulations results reveal symmetrical trust levels between two trading agents, based on which the degree of trust relationship in each pair of trading agents as well as the resulting collaboration patterns in the entire supply network emerge. Also, it is shown that agents' decision-making behavior based on the trust relationship can contribute to the reduction in the variability of inventory levels. This result can be explained by the fact that mutual trust relationship based on the past experiences of trading diminishes an agent's uncertainties about the trustworthiness of its trading partners and thereby tends to stabilize its inventory levels.

Suggested Citation

  • Whan-Seon Kim, 2009. "Effects of a Trust Mechanism on Complex Adaptive Supply Networks: An Agent-Based Social Simulation Study," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(3), pages 1-4.
    • Handle: RePEc:jas:jasssj:2009-6-2
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    References listed on IDEAS

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    Cited by:

    1. Rozhin Doroudi & Pedro Sequeira & Stacy Marsella & Ozlem Ergun & Rana Azghandi & David Kaeli & Yifan Sun & Jacqueline Griffin, 2020. "Effects of trust-based decision making in disrupted supply chains," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-21, February.
    2. Shu-Heng Chen & Bin-Tzong Chie & Tong Zhang, 2015. "Network-Based Trust Games: An Agent-Based Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(3), pages 1-5.
    3. Jarratt, Denise & Ceric, Arnela, 2015. "The complexity of trust in business collaborations," Australasian marketing journal, Elsevier, vol. 23(1), pages 2-12.
    4. Juan M Hernández & Carmen Pedroza-Gutiérrez, 2019. "Estimating the influence of the network topology on the agility of food supply chains," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-21, July.
    5. Hou, Yunzhang & Wang, Xiaoling & Wu, Yenchun Jim & He, Peixu, 2018. "How does the trust affect the topology of supply chain network and its resilience? An agent-based approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 229-241.
    6. Morteza Alaeddini & Julie Dugdale & Paul Reaidy & Philippe Madiès, 2023. "Exploring Credit Relationship Dynamics in an Interbank Market Benefiting from Blockchain-based Distributed Trust: Insights from an Agent-based Model," Post-Print hal-04266077, HAL.
    7. Doloswala, Kalika Navin, 2014. "Eroding trust – An agent based model to explore how trust flows," Australasian marketing journal, Elsevier, vol. 22(1), pages 51-53.
    8. Paola Tubaro, 2011. "Computational Economics," Chapters, in: John B. Davis & D. Wade Hands (ed.), The Elgar Companion to Recent Economic Methodology, chapter 10, Edward Elgar Publishing.
    9. repec:eur:ejfejr:7 is not listed on IDEAS
    10. Gao, Lin, 2017. "Between Trust and Performance: Exploring Socio-Economic Mechanisms on Directed Weighted Regular Ring with Agent-Based Modeling," MPRA Paper 78428, University Library of Munich, Germany.
    11. Marcus A. Bellamy & Rahul C. Basole, 2013. "Network analysis of supply chain systems: A systematic review and future research," Systems Engineering, John Wiley & Sons, vol. 16(2), pages 235-249, June.
    12. Gao, Lin, 2016. "Trust and Performance: Exploring Socio-Economic Mechanisms in the “Deep” Network Structure with Agent-Based Modeling," MPRA Paper 75214, University Library of Munich, Germany.

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